aspires to model people as cognitive machines, whose internal mechanisms
parallel those we build into digital computers. An expression of this is
Newell and Simon's physical symbol system hypothesis. Newell's conception was
inspirational for the founding text on HCI as a discipline of cognitive
engineering (Card, Moran, Newell: "The psychology of Human Computer
The key assumption is that essential aspects of thought can be captured in a
formal symbolic representation. So we can create intelligent programs and we
can design systems that optimize human interaction.
The focus is not on modeling intelligent internal workings, but on the
interactions between a person and the enveloping environment.
These bring along a shift in what kind of understanding is pursues. In design
there often aren't predictive models of human interpretation and behavior.
Design doesn't requires a calculation to see if "it works", but an iterative
process of prototype testing and refinement.
"Enlightened trial and error outperforms the planning of flawless intellect."
Today's there is a debate about the roles of analysis and design in creating
new interfaces and understanding the way people interact with them. There is a
need for a "T-shaped" approach:
- - deep analytical understanding of a scientific or technological domain
- | ability to bring design thinking to problems in a holistic way,
recognizing the limitation of analysis and developing the ability to work
effectively in problem areas that carry the unavoidable complexity and messiness
of the human situation.
Disclaimer: I wrote these summaries to help me remember the
content and the main ideas of the paper. Since I am interested in certain
aspects, I may leave out others.